This work demonstrates that the integration of variable-speed wind systems with doubly fed induction generators (DFIG) and a four-quadrant AC-to-AC converter connected to the rotor windings increases ...the transient stability margin of the electrical grids, when compared with the case where the fixed speed wind systems with cage generators are used. It is due to the influence of the two dedicated rotor current regulators of the DFIG on the dynamic behavior of the other generators in the system. Besides, adequate models to represent the behavior of the DFIG in transient stability studies are presented. From the simulation results, some important conclusions can be extracted to guide the integration of the wind farms on weak or strong grids.
This study presents some data-mining experiments applied to electric power systems with the aim of extracting knowledge from historical data produced by the supervision, control and data acquisition ...system of a hydroelectric plant in Brazil. In the first experiment, statistical analysis is performed on discrete events such as Boolean events, alarms, commands, set-points and analogue quantities as electrical frequency, to display relevant aspects of the electrical system operation. Next, the results of an experiment performed on discrete events from associations describing relationships patterns among items in a database are presented. In the third experiment, a decision tree is used to reveal relationships among several analogue variables as: the relationship between the downstream water level and generated power. These experiences contribute to successfully show the datamining applicability to power systems, to improve the management of hydroelectric power plants operation, maintenance and planning, besides also contributing to establish a culture of its usage in the electrical industry.
This work presents a design procedure based on an evolutionary computation, more specifically on a genetic algorithm combined with the formal pole placement project, to obtain optimal controllers to ...the rotor-side converter of doubly fed induction generators (DFIGs), in variable-speed wind generation systems connected to the electrical grid. With this procedure it is intended to improve the global system dynamic behaviour during and after the fault period, also increasing the transient stability margin of the power system and the fault ride-through capability. The control action of the DFIG converters is accomplished by proportional and integral controllers, whose gains' adjustment is not a trivial task, because of the high complexity of the system. The results obtained confirm the efficiency of the proposed control design procedure.
This work presents the use of the wavelet transform and computational intelligence techniques to quantify voltage short-duration variation in electric power systems, with respect to time duration and ...magnitude. The wavelet transform is used to determine the event duration, as well as for obtaining a characteristic curve relating the signal norm as function of the number of cycles for a waveform without disturbance that is used as reference for the calculation of the magnitude of the event. A generalized regression neural network (GRNN) is used to interpolate not stored points of the characteristic curve. The method is part of a process to automate the post operation signal analysis in electric power systems, and it is used to quantify the voltage short-duration variation magnitude of previously selected signals. The method has been shown efficient, and some results obtained from the application of this method to power system real signals are presented.
This paper proposes a new approach to fault diagnosis in electrical power systems, which presents an aspect little explored in the literature that is the protective device failure detection together ...with the fault section estimation, since the majority of the methodologies so far proposed to fault diagnosis are limited to the fault section estimation alone. The proposed methodology makes use of operation states of protective devices as well as information related to the protection philosophy. Initially, these data undergo a preprocessing step to convert the format of 0 and 1 to percentage values. The conversion to percentage values allows the use of artificial neural networks, whose numbers of inputs do not depend on the number of alarms of the protection philosophy, or the type of bus arrangement or the number of circuit breakers. This allows the same set of neural networks to be trained and applied in different power systems with different protection schemes and bus arrangements. The proposed system has five neural networks, each containing few neurons and requiring 30 μs to perform fault diagnosis. The proposed system was trained considering the IEEE 57-bus system, containing different selective protection schemes, and subsequently tested in the IEEE 14-bus, 30-bus, and 118-bus systems, and Eletronorte 230-kV real power system.
This work presents a hybrid method to solve the protective devices allocation problem in electric distribution systems. Current methods only consider optimization results, without taking into account ...standards established by electric energy companies. These standards reflect distribution systems particularities observed by these companies. Firstly, recloser placementis determined through an optimization process, aiming to reduce reliability indices. Fuse links are placed according to heuristic rules established by electric companies. To validate the proposed methodology, a comparison with three other references from the literature is carried out, showing good results and proving the method's effectiveness.
The assessment of step voltage regulator (SVR) operation in active distribution networks requires computational analysis tools capable of tackling the emerging technical challenges. Conventional load ...flow (CLF), quasi-static time series (QSTS) and dynamic simulations are typically employed to investigate high-penetration distributed generation (DG) interconnection impacts. Regarding the SVR runaway condition phenomenon, however, a consensus has yet to be reached on the most cost-effective simulation technique for capturing and reproducing the correct sequence of events. This work presents a comparative study of the CLF, QSTS and dynamic simulation techniques through modelling and analysis of two SVR-controlled test-feeders, in order to evaluate each approach performance in addressing scenarios of DG-caused reverse active power flow. Detailed descriptions of feeder voltage profile and SVR tap operations are provided to facilitate understanding of the mechanisms that characterize SVR runaway condition, as well as the advantages and drawbacks of each of the studied simulation techniques.
The recent expansion of multidrug-resistant (MDR) pathogens poses significant challenges in treating healthcare-associated infections. Although antibacterial resistance occurs by numerous mechanisms, ...active efflux of the drugs is a critical concern. A single species of efflux pump can produce a simultaneous resistance to several drugs. One of the best-studied efflux pumps is the TtgABC: a tripartite resistance-nodulation-division (RND) efflux pump implicated in the intrinsic antibiotic resistance in Pseudomonas putida DOT-T1E. The expression of the TtgABC gene is down-regulated by the HTH-type transcriptional repressor TtgR. In this context, by employing quantum chemistry methods based on the Density Functional Theory (DFT) within the Molecular Fragmentation with Conjugate Caps (MFCC) approach, we investigate the coupling profiles of the transcriptional regulator TtgR in complex with quercetin (QUE), a natural polyphenolic flavonoid, tetracycline (TAC), and chloramphenicol (CLM), two broad-spectrum antimicrobial agents. Our quantum biochemical computational results show the: i convergence radius, ii total binding energy, iii relevance (energetically) of the ligands regions, and iv most relevant amino acids residues of the TtgR-QUE/TAC/CLM complexes, pointing out distinctions and similarities among them. These findings improve the understanding of the binding mechanism of effectors and facilitate the development of new chemicals targeting TtgR, helping in the battle against the rise of resistance to antimicrobial drugs. These advances are crucial in the ongoing fight against rising antimicrobial drug resistance, providing hope for a future where healthcare-associated infections can be more beneficially treated.
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